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2021 ; 51
(6
): 3936-3951
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An imperialist competition algorithm using a global search strategy for physical
examination scheduling
#MMPMID34764571
Yu H
; Li JQ
; Zhang L
; Duan P
Appl Intell (Dordr)
2021[]; 51
(6
): 3936-3951
PMID34764571
show ga
The outbreak of the novel coronavirus clearly highlights the importance of the
need of effective physical examination scheduling. As treatment times for
patients are uncertain, this remains a strongly NP-hard problem. Therefore, we
introduce a complex flexible job shop scheduling model. In the process of
physical examination for suspected patients, the physical examiner is considered
a job, and the physical examination item and equipment correspond to an operation
and a machine, respectively. We incorporate the processing time of the patient
during the physical examination, the transportation time between equipment, and
the setup time of the patient. A unique scheduling algorithm, called imperialist
competition algorithm with global search strategy (ICA_GS) is developed for
solving the physical examination scheduling problem. A local search strategy is
embedded into ICA_GS for enhancing the searching behaviors, and a global search
strategy is investigated to prevent falling into local optimality. Finally, the
proposed algorithm is tested by simulating the execution of the physical
examination scheduling processes, which verify that the proposed algorithm can
better solve the physical examination scheduling problem.